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docs: Add explanation on how to use Hugging Face embeddings (#22118)
- **Description:** I've added a tab on embedding text with LangChain using Hugging Face models to here: https://python.langchain.com/v0.2/docs/how_to/embed_text/. HF was mentioned in the running text, but not in the tabs, which I thought was odd. - **Issue:** N/A - **Dependencies:** N/A - **Twitter handle:** No need, this is tiny :) Also, I had a ton of issues with the poetry docs/lint install, so I haven't linted this. Apologies for that. cc @Jofthomas - Tom Aarsen
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@ -75,6 +75,31 @@ Otherwise you can initialize without any params:
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from langchain_cohere import CohereEmbeddings
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from langchain_cohere import CohereEmbeddings
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embeddings_model = CohereEmbeddings()
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embeddings_model = CohereEmbeddings()
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```
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</TabItem>
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<TabItem value="huggingface" label="Hugging Face">
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To start we'll need to install the Hugging Face partner package:
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```bash
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pip install langchain-huggingface
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```
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You can then load any [Sentence Transformers model](https://huggingface.co/models?library=sentence-transformers) from the Hugging Face Hub.
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```python
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from langchain_huggingface import HuggingFaceEmbeddings
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embeddings_model = HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
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```
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You can also leave the `model_name` blank to use the default [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) model.
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```python
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from langchain_huggingface import HuggingFaceEmbeddings
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embeddings_model = HuggingFaceEmbeddings()
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```
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```
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</TabItem>
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</TabItem>
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